Determining resting heart rate using wearable device

ABSTRACT

A wearable device is described. The wearable device comprises: a device body configured to be secured in contact with a subject; a first sensor borne by the device body that is activatable to measure a heart rate of the subject; and control logic configured to activate the first sensor during a monitoring period during which the subject is determined to be in a sleep period.

BACKGROUND

Resting heart rate is the number of contractions of the heart that occurduring a period of time, such as one minute, while the body is at rest.Resting heart rate is regarded as a significant indicator of one's levelof fitness, as a strong heart can pump more blood with each contraction,thus needing to contract fewer times in a minute to provide adequateblood flow. Resting heart rate can also be an indicator of healthcondition, as resting heart rate tends to increase with fever. As such,many people are interested in determining their resting heart rate.

One way of measuring resting heart rate is to count contractions—such asby palpating an artery—for one minute immediately upon waking. Anotherway of measuring resting heart rate is to wear an electrocardiogram(“ECG”) monitor during sleep as part of a medical sleep study.

SUMMARY

This summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This summary is not intended to identify key factors oressential features of the claimed subject matter, nor is it intended tobe used to limit the scope of the claimed subject matter.

A wearable device is described. The wearable device comprises: a devicebody configured to be secured in contact with a subject; a first sensorborne by the device body that is activatable to measure a heart rate ofthe subject; and control logic configured to activate the first sensorduring a monitoring period during which the subject is determined to bein a sleep period.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a network diagram showing an environment in which the facilityoperates in some embodiments.

FIG. 2 is a block diagram showing some of the components typicallyincorporated in at least some of the computer systems and other deviceson which the facility operates.

FIG. 3 is a hardware diagram showing a visual heart rate sensor used bythe facility in some embodiments to capture heart rate samples.

FIG. 4 is a flow diagram showing steps typically performed by thefacility in order to obtain and process data to determine a subject'sresting heart rate.

FIG. 5 is a timing diagram showing the relationship of sampling periodsto sampling cycles.

FIG. 6 is a timing diagram showing a set of samples collected by thefacility during sampling period 511 shown in FIG. 5.

FIG. 7 is a display diagram showing a sample display that conveys aresting heart rate determined by the facility.

DETAILED DESCRIPTION

There are a number of significant disadvantages posed by conventionalapproaches to measuring resting heart rate. Manually counting one'spulse on waking can be difficult for some people, as it requires: havingthe presence of mind on waking to take directed action; having atimepiece on hand; locating an artery; and maintaining a count whilewatching for expiration of a minute. Even more significantly, becausethe subject is awake at the time of the measurement, and must takeaction in order to perform the measurement, the measurement often doesnot reflect the subject's lowest heart rate, as wakefulness and theactivity of measurement elevate the subject's heart rate relative tovarious points during the sleep cycle.

For this reason, the ECG measurement during a medical sleep study, attimes when the subject is sleeping, is regarded by many as moreaccurate. Such sleep studies can be extremely expensive, however,typically costing thousands of dollars. They are also unpleasant for thesubject, requiring them to enter an unfamiliar, clinical setting andattempt to sleep, typically with several kinds of sensors attached totheir bodies, cameras and other instruments observing them, etc. Thisunpleasantness can impair the accuracy of the resting heart ratemeasurement, as it can interfere with the subject's ability to reachdeeper stages of sleep, at which lower heart rates occur. Also, it isimpractical to perform sleep studies on a recurring basis to trackchanges in resting heart rate over time.

In order to overcome these disadvantages of conventional approaches tomeasuring resting heart rate, a software and/or hardware facility isdisclosed for determining a subject's resting heart rate during sleepusing a wearable device worn by the subject.

In some embodiments, the wearable device worn by the subject is a typeof wearable device that is, in different respects, suitable to be wornthroughout the day and night. In some embodiments, the wearable deviceis a band that wraps around part of the subject's body, such as aroundthe subject's wrist. In a variety of embodiments, this device performs avariety of functions in addition to determining resting heart rate,including various combinations of the following: tell time; count steps;prompt through a fitness workout routine; measure distance traveled;provide travel directions; measure a time period, such as a time periodduring which the subject is exercising; track sleep time and/or quality;measure light exposure, such as exposure to light in the ultravioletfrequency band; provide alarms and calendar notifications; take or viewphotos; send or receive email messages, text messages, instant messages,and/or voice calls; access news, weather, social network content, and/orother content; interact, such as by voice, with an automated assistant;serve electronic identification, loyalty program, and/or paymentfunctions; etc.

In some embodiments, the device has one or more sensors usable to detectbody phenomena connected to the contraction of the heart. In someembodiments, the device has an optical heart rate sensor thatilluminates the subject's skin with a light source and measures—such aswith a photodiode, an image sensor of another type, or a light sensor ofanother type—its change in light absorption resulting from thedistension of arteries and arterioles in response to cardiaccontractions. In some embodiments, the device includes one or more ECGsensors that measure electrical signals produced by the heart. In someembodiments, the device includes one or more bioimpedance sensors thatmeasure changes in the impedance level of the subject's skin.

In some embodiments, the facility optimizes the energy consumed in thewearable device by collecting heart rate data only during limitedperiods. In some embodiments, the facility collects heart rate data foruse in determining resting heart rate during a period when the subjecthas explicitly indicated that the subject is sleeping, or is attemptingto sleep. In some embodiments, the facility collects heart rate data foruse in determining resting heart rate during a period during which thefacility infers that the subject is asleep. In some embodiments, thefacility collects heart rate data consistently over time, and selectsheart rate data for use in determining resting heart rate based on aretrospective analysis of whether the subject was asleep, and/ordetermines resting heart rate from this heart rate data without regardfor subject sleep patterns. In some embodiments, the facility activatesthe device's heart rate sensors only during limited sampling periods. Asexamples, in various embodiments, the facility activates the device'sheart rate sensors only for a one-minute or two-minute sampling periodduring each sampling cycle, such as a 10-minute sampling cycle.

In some embodiments, the facility uses various techniques for filteringquestionable heart rate data that may correspond to sensor or othersampling errors, or may correspond to times when the subject was notsleeping, or was not sleeping soundly. In some embodiments, thefacility's sample filtering techniques involves assigning each sample aquality measure. In some embodiments, the facility determines a sample'squality measure at least in part based upon whether the sample's heartrate falls within a plausible heart rate range, or within a plausibleresting heart rate range. In some embodiments, the facility determines asample's quality measure at least in part based upon various indicia,using a variety of the device's sensors, of whether the subject isresting, trying to rest, sleeping, or trying to sleep.

In some embodiments, the facility outputs the resting heart rate itdetermines for the subject in a variety of ways, such as by presentingit textually and/or graphically on a variety of devices, generating achart or graph showing it over time or in comparison to other subjects'resting heart rates, storing it in the database, using it in healthanalysis processes, etc.

By behaving in some or all of the ways described above, the facilityprovides useful health information in a manner that is accurate,convenient, inexpensive, and nonintrusive, in a way that extends thebattery life and/or reduces the energy storage requirements of thewearable device.

FIG. 1 is a network diagram showing an environment in which the facilityoperates in some embodiments. A wearable device 100 can be worn by thesubject, such as around the subject's wrist. The wearable device has oneor more kinds of sensors suitable for measuring the subject's heartrate. The wearable device stores heart rate measurements, or “samples,”that it obtains from the subject. In various embodiments, these samplesare stored and/or processed in various locations, including on thewearable device; on a connected device 110 as discussed below, and/or ona server 130 with which the connected device communicates via a networksuch as the Internet 120. The wearable device and the connected deviceare connected in one or more ways, such as via a wired or guided opticalconnection, via an unguided optical or radio wireless connection, etc.In various embodiments, the connected device is of a variety ofdifferent device types, including a mobile phone, a tablet, a laptopcomputer, a desktop computer, an automobile computer, a Wi-Fi router oraccess point, a cellular network transceiver, etc.

The wearable device may be implemented in any number of different formfactors such as jewelry, clothing, or an assistive device. Wearabledevices implemented as jewelry include wearable devices that do notsubstantially cover a portion of the body and have aesthetic value butmay have limited functionality other than the functionality of thewearable device. Jewelry includes watches, bracelets, rings, earrings,pendants, necklaces, and the like. Wearable devices implemented asclothing include wearable devices that cover a portion of the body andshare functionality with the analogous article of clothing. Examples ofclothing include gloves, shoes, hats, headbands, wristbands, anklebands, and the like. Wearable devices implemented as an assistive deviceinclude functionality that addresses a medical need of an individual.Assistive devices include glasses, hearing aids, insulin pumps, asingle-purpose device that performs monitoring of the physiological datawithout additional functions, and the like. In some embodiments, thewearable device is said to have a portion called a “body,” by which thewearable device's heart rate sensor is borne.

While various embodiments are described in terms of the environmentdescribed above, those skilled in the art will appreciate that thefacility may be implemented in a variety of other environments includinga single, monolithic computer system, as well as various othercombinations of computer systems or similar devices connected in variousways.

FIG. 2 is a block diagram showing some of the components typicallyincorporated in at least some of the computer systems and other deviceson which the facility operates. In various embodiments, these computersystems and other devices 200 can include server computer systems,desktop computer systems, laptop computer systems, mobile phones,personal digital assistants, televisions, cameras, automobile computers,electronic media players, etc. In various embodiments, the computersystems and devices include zero or more of each of the following: acentral processing unit (“CPU”) 201 for executing computer programs; acomputer memory 202 for storing programs and data while they are beingused; a persistent storage device 203, such as a hard drive or flashdrive for persistently storing programs and data; a computer-readablemedia drive 204, such as a floppy, CD-ROM, or DVD drive, for readingprograms and data stored on a computer-readable medium; and a networkconnection 205 for connecting the computer system to other computersystems to send and/or receive data, such as via the Internet or anothernetwork and its networking hardware; and one or more input/outputdevices 206, including physiological sensors of various kinds, motionsensors, microphones and speakers, orientation sensors, temperaturesensors, pressure sensors, humidity sensors, a visual display, adigitizer for detecting touches between the visual display and a user'sfinger or other object; etc. While computer systems configured asdescribed above are typically used to support the operation of thefacility, those skilled in the art will appreciate that the facility maybe implemented using devices of various types and configurations, andhaving various components.

FIG. 3 is a hardware diagram showing an optical heart rate sensor usedby the facility in some embodiments to capture heart rate samples. Insome embodiments, the optical heart rate sensor 310 is incorporated intoa wearable device 300, and includes one or more illumination sources311, such as light-emitting diodes, as well as a photo diode 312—or animage sensor or light sensor of another type. The optical heart ratesensor is directed toward the subject's skin, and the light sourcesilluminate the skin, while the sensor 312 measures changes in lightabsorption in the skin. In a variety of embodiments, the facility uses avariety of different sensors for capturing heart rate samples.

FIG. 4 is a flow diagram showing steps typically performed by thefacility in order to obtain and process data to determine a subject'sresting heart rate. In some embodiments, the facility performs the stepsshown in FIG. 4 during a monitoring period, such as a monitoring periodduring which the subject is determined to be seeking to rest, resting,seeking to sleep, or sleeping. In some embodiments, some or all of thesteps of FIG. 4 are referred to as “control logic.”

In some embodiments, the facility determines the status of individual asresting or sleeping based on a manual indication from the subjectwhenever he or she prepares to sleep. In some embodiments, the subjectactivates a special-purpose input device of the wearable device, such asa physical button, to provide this manual indication. In someembodiments, the subject uses a general-purpose input device for thispurpose, such as by activating a visual user input tile on a touchscreen, or by speaking a verbal command. In some embodiments, the end ofresting is also indicated manually when the subject wakes. Resting orsleeping status may be detected automatically by the wearable device, orretrospectively by another device. In various embodiments, the wearabledevice uses any number of different sensors to detect that the subjectis resting or sleeping. For example, in some embodiments, a motionsensor, such as an accelerometer or gyroscope, in the wearableelectronic device detects motion of the individual, and the facilityuses an absence of motion to infer that the individual is resting. Invarious embodiments, the facility also uses measurement of physiologicalfeatures such as skin temperature, heart rate, and/or respiration rateto infer a state of rest or sleep. Because skin temperature, heart rate,and respiration rate all decrease during normal sleep, in someembodiments, the facility uses these measures to identify theindividual's sleep and wake cycle. In some embodiments, the facilityuses a wearable device that detects brain waves such as anelectroencephalogram (EEG) to determine that the subject is sleeping. Insome embodiments, the facility infers the status of the individual asresting or sleeping based on time; for example, in some embodiments, thefacility assumes that the subject is resting or asleep between the timesof 1 AM and 5 AM. In some embodiments, some or all of these techniquesfor determining whether the subject is in a sleep period are referred toas “analysis logic.”

In step 401, the facility initializes a current minimum result value inwhich the facility stores the lowest heart rate thus far attributed tothe subject during analysis session. In steps 402 -413, the facilityloops through each sampling cycle, such as a sampling cycle 10 minuteslong. Steps 403-412 describe steps performed during the current samplingcycle's sampling period, such as a sampling period two minutes long, ora sampling period one minute long. In step 403, the facility activatesthe device's heart rate sensor. The facility repeats steps 404 -411 foreach group of samples collected by the facility during the currentcycle's sampling period. In step 405, the facility collects a group ofsamples. In some embodiments, a group is defined as a certain number ofsamples. In some embodiments, samples are collected at a fixedfrequency, such as once per second. In some embodiments, in order tocollect a group of samples, the facility monitors the samples beingoutputted by the heart rate sensor, and waits until a sample is receivedthat is determined to be of adequate quality. In some embodiments, thefacility determines a numerical quality measure for each sample that ituses to assess whether each sample is of adequate quality for use. Somefactors used in determining a sample's measure of quality include theextent to which a sample's heart rate is within a reasonable range, suchas between 35 beats per minute and 85 beats per minute; the degree towhich various sensors indicate that the subject is asleep, such asmotion sensors indicating that the only motions the device is undergoingare consistent with the subject being asleep; whether sounds received bythe microphone are consistent with the user being asleep; whether deviceorientation determined by orientation sensors are consistent with theuser being asleep; whether sensors reflecting the positioning of thedevice and its heart rate sensors reflect that these are correctlypositioned relative to the subject's body for capturing accuratesamples; whether the level of light reported by outward-facing lightsensors is consistent with a sleeping environment; etc. In someembodiments, in order to collect a group of samples, the facility groupcollects a group of 20 contiguous samples that begin with the nextsample having an adequate quality measure.

In step 406, the facility identifies samples in the collected in step405 that are of adequate quality, such as those having a quality measurethat exceeds a quality level threshold. In step 407, if the percentageof samples in the group determined in step 406 to be of adequate qualityexceeds a threshold percentage, then the facility continues in step 408,else the facility continues in step 411. In step 408, the facilityaggregates the samples of the group determined to be of adequate qualityin step 406, such as by computing the mean, median, mode, etc. of thesesamples. In step 409, if the aggregated value determined in step 408 islower than the current minimum result, then the facility continues instep 410, else the facility continues in step 411. In step 410, thefacility blends the aggregated value determined in step 408 into thecurrent minimum result. Where the current minimum result is in itsinitialized state from step 401, the facility simply substitutes theaggregate value from step 408 for this initialized state. Otherwise, thefacility computes a weighted average of the current minimum result andthe aggregated value determined in step 408, such as by adding 40% ofthe aggregated value to 60% of the current minimum result.

In step 411, if the sampling period has not ended, the facilitycontinues in step 404 to collect and process the next group of samples.In step 412, on the expiration of the current sampling period, thefacility disables the heart rate sensor in the device. In step 413, thefacility continues in step 402 to reactivate the sensor at the beginningof the next sampling cycle period. In step 414, such as at the end ofthe night, or at an arbitrary time, or at a time when various sensorsreflect that a sleeping period has ended, or at a time when the userexplicitly indicates that sleep has ended, the facility reports thecurrent value of the current minimum result as modified in step 410.After step 414, these steps conclude.

Those skilled in the art will appreciate that the steps shown in FIG. 4and in each of the flow diagrams discussed below may be altered in avariety of ways. For example, the order of the steps may be rearranged;some steps may be performed in parallel; shown steps may be omitted, orother steps may be included; a shown step may divided into substeps, ormultiple shown steps may be combined into a single step, etc.

FIG. 5 is a timing diagram showing the relationship of sampling periodsto sampling cycles. It can be seen that, in FIG. 5, each of samplingcycles 510 and 520 is 10 minutes long. For example, sampling cycle 510lasts from 22:10:00 to 22:20:00. Each of sampling periods 511 and 521 isthe first two minutes of the sampling cycle that contains it. Forexample, sampling period 511 lasts between 22:10:00 and 22:12:00.

FIG. 6 is a timing diagram showing a set of samples collected by thefacility during sampling period 511 shown in FIG. 5. Each samplecollected by the facility is represented by a vertical line at adifferent point on the timeline whose height reflects the sample'squality measure. These samples are reflected in numerical form in Table1 below. This table shows, for each of the samples: the time at whichthe sample was collected; the quality measure attributed to the sample;and the heart rate measured in the sample. For example, the first row ofTable 1 indicates that, at time 22:10:01, a heart rate of 15 beats perminute was measured, and attributed a sample quality value of 7. Theheart rates shown in Table 1 are for illustrative purposes only, and donot necessarily correspond to a particular subject having a particularfitness or health level.

TABLE 1 time sample heart rate sample quality 22:10:01 15 7 22:10:02 8 422:10:03 48 16 22:10:04 51 15 22:10:05 50 14 22:10:06 47 16 22:10:07 4614 22:10:08 47 11 22:10:09 46 8 22:10:10 48 15 22:10:11 46 9 22:10:12 4813 22:10:13 47 15 22:10:14 47 15 22:10:15 47 13 22:10:16 44 14 22:10:1749 15 22:10:18 48 11 22:10:19 12 8 22:10:20 48 12 22:10:21 47 1622:10:22 48 13 22:10:23 49 12 22:10:24 50 14 22:10:25 51 12 22:10:26 5015 22:10:27 51 15 22:10:28 49 13 22:10:29 47 12 22:10:30 49 15 22:10:3149 13 22:10:32 51 13 22:10:33 53 14 22:10:34 58 3 22:10:35 59 6 22:10:3649 14 22:10:37 50 13 22:10:38 49 13 22:10:39 48 12 22:10:40 47 1322:10:41 49 12 22:10:42 88 8 22:10:43 92 5 22:10:44 103 7 22:10:45 155 222:10:46 132 8 22:10:47 119 5 22:10:48 115 6 22:10:49 100 8 22:10:50 969 22:10:51 47 13 22:10:52 45 14 22:10:53 46 12 22:10:54 45 14 22:10:5546 12 22:10:56 45 14 22:10:57 45 12 22:10:58 47 13 22:10:59 44 1422:11:00 45 14 22:11:01 45 15 22:11:02 46 15 22:11:03 45 15 22:11:04 4514 22:11:05 44 13 22:11:06 44 12 22:11:07 45 14 22:11:08 45 14 22:11:0946 12 22:11:10 8 8

Beginning at time 22:10:00 when sampling period 511 begins, the facilityobserves samples until it reaches the next sample whose quality measureexceeds a quality threshold 610. In Table 1, the quality thresholdcorresponds to the quality value 10. As can be seen in both FIG. 6 andTable 1, the first such sample occurs at time 22:10:03, which, unlikethe samples at times 22:10:01 and 22:10:02, has a quality measure thatexceeds 10. Sample group 620 then includes the sample at 22:10:03, aswell as the succeeding 19 samples. These are shown below in Table 2.

TABLE 2 time sample heart rate sample quality 22:10:03 48 16 22:10:04 5115 22:10:05 50 14 22:10:06 47 16 22:10:07 46 14 22:10:08 47 11 22:10:0946 8 22:10:10 48 15 22:10:11 46 9 22:10:12 48 13 22:10:13 47 15 22:10:1447 15 22:10:15 47 13 22:10:16 44 14 22:10:17 49 15 22:10:18 48 1122:10:19 12 8 22:10:20 48 12 22:10:21 47 16 22:10:22 48 13

After collecting sample group 620, the facility identifies the samplesin the sample group that are of an adequate quality level, such as thosethat exceed the quality threshold of 10.

Table 3 below shows the samples of sample group 620 whose quality thefacility determines to be adequate. By comparing Table 3 to Table 2, itcan be seen that samples from the following times have been removed asnot being of adequate quality: 22:10:09, 22:10:11, and 22:10:19.

TABLE 3 time sample heart rate sample quality 22:10:03 48 16 22:10:04 5115 22:10:05 50 14 22:10:06 47 16 22:10:07 46 14 22:10:08 47 11 22:10:1048 15 22:10:12 48 13 22:10:13 47 15 22:10:14 47 15 22:10:15 47 1322:10:16 44 14 22:10:17 49 15 22:10:18 48 11 22:10:20 48 12 22:10:21 4716 22:10:22 48 13 mean: 47.6 current minimum result: 47.6

In various embodiments, the facility applies various aggregationfunctions to the remaining sample heart rates, such as mean, median,mode, minimum, etc. In the example, the facility computes the mean ofthe remaining sample heart rates as a means of filtering out aberrantlylow samples that would be given greater credence by the minimumaggregation function, arriving at a mean of 47.6. As the sample group620 is the first sample group determined in this resting heart ratedetermination period, the facility simply copies this mean value of 47.6to the current minimum result.

Table 4 below shows the samples of sample group 630 that the facilitydeems to be of adequate quality. Table 4 further shows a mean heart rateof 49.5 beats per minute. Because this mean value of 49.5 is larger thanthe current minimum result of 47.6, the facility does not change thecurrent minimum result in response to sample group 630.

TABLE 4 time sample heart rate sample quality 22:10:23 49 12 22:10:24 5014 22:10:25 51 12 22:10:26 50 15 22:10:27 51 15 22:10:28 49 13 22:10:2947 12 22:10:30 49 15 22:10:31 49 13 22:10:32 51 13 22:10:33 53 1422:10:36 49 14 22:10:37 50 13 22:10:38 49 13 22:10:39 48 12 22:10:40 4713 22:10:41 49 12 mean: 49.5 current minimum result: 47.6

Table 5 below shows the samples of sample group 640 of adequate quality.These have a mean heart rate of 45.3 beats per minute. Because the meanof 45.3 beats per minute of sample group 640 is less than the currentminimum result of 47.6, the facility blends the current mean of 45.3into the current minimum result. In general, the facility weights themean of the current sample group against the current minimum result in aconsistent way to moderate the speed with which the current minimumresult adapts toward the current sample group mean. In some embodiments,the facility weights the current minimum result higher than the currentsample group mean, such as at 60% vs. 40%. In the example, the facilityobtains a new current minimum result of 47.6 to reach a new currentminimum result of 46.7 by weighting the mean for sample group 640 at 40%and the prior current minimum result at 60%.

TABLE 5 time sample heart rate sample quality 22:10:51 47 13 22:10:52 4514 22:10:53 46 12 22:10:54 45 14 22:10:55 46 12 22:10:56 45 14 22:10:5745 12 22:10:58 47 13 22:10:59 44 14 22:11:00 45 14 22:11:01 45 1522:11:02 46 15 22:11:03 45 15 22:11:04 45 14 22:11:05 44 13 22:11:06 4412 22:11:07 45 14 22:11:08 45 14 22:11:09 46 12 mean: 45.3 currentminimum result: 46.7

FIG. 7 is a display diagram showing a sample display that conveys aresting heart rate determined by the facility. In a variety ofembodiments, the facility causes this display to be presented via avariety of display devices. It can be seen that the display 700 includesa timeline, along which the subject's minimum resting heart rate 731 isplotted. The timeline contains two time index components: a time indexcomponent 710 showing the day and date when the sleep period began, anda time index component 720 showing the day and date when the sleepperiod ended. The display also includes a scale 730 that reflects theminimum resting heart beat that was determined by the facility duringeach of the sleep periods. In various embodiments, the display hasvarious other characteristics, such as the ability for a user to hover amouse cursor over a spot on plot 731, or touch such a spot with theirfinger, to have displayed a numerical value of the heart minimum restingheart beat determined on that day.

In some embodiments, the facility stores the resting heart rate itdetermines for a subject in a table, such as a table made up of entrieseach containing a determined resting heart rate, and an indication ofwhen the samples were collected that were used in the determination.

In some embodiments, the facility provides a wearable device. Thewearable device comprises: a device body configured to be secured incontact with a subject; a first sensor borne by the device body that isactivatable to measure a heart rate of the subject; and control logicconfigured to activate the first sensor during a monitoring periodduring which the subject is determined to be in a sleep period.

In some embodiments, the facility provides a computer-readable mediumhaving contents configured to cause a computing system to: initialize acurrent minimum heartbeat result; during a period when a wearer of awearable device is determined to be in a sleep period: for each of aplurality of sampling periods: obtain via the device a sequence of heartrate samples for the wearer; for each of the samples, assess whether thesample is usable; if at least the threshold percentage of the samplesare assessed to be usable: aggregate the samples assessed to be usable;and if the aggregated samples are smaller than the current minimumheartbeat result, blend the aggregated samples into the current minimumheartbeat result.

In some embodiments, the facility provides a method in a computingsystem, comprising: initializing a current minimum heartbeat result;during a period when a wearer of a wearable device is determined to bein a sleep period: for each of a plurality of sampling periods:obtaining via the device a sequence of heart rate samples for thewearer; for each of the samples, assessing whether the sample is usable;if at least the threshold percentage of the samples are assessed to beusable: aggregating the samples assessed to be usable; and if theaggregated samples are smaller than the current minimum heartbeatresult, blending the aggregated samples into the current minimumheartbeat result.

In some embodiments, the facility provides a computer-readable mediumstoring a resting heart rate data structure for a subject. The datastructure comprises: a plurality of entries, each entry corresponding toa different sleep period of the subject, each entry comprising: aquantitative indication of a resting heart rate for the subject, theindication having been generated from heart rate samples captured fromthe subject by a wearable device during the sleep period.

It will be appreciated by those skilled in the art that theabove-described facility may be straightforwardly adapted or extended invarious ways. While the foregoing description makes reference toparticular embodiments, the scope of the invention is defined solely bythe claims that follow and the elements recited therein.

1. A wearable device, comprising: a device body configured to be securedin contact with a subject; a first sensor borne by the device body thatis activatable to measure a heart rate of the subject; and control logicconfigured to activate the first sensor during a monitoring periodduring which the subject is determined to be in a sleep period.
 2. Thewearable device of claim 1 wherein the first sensor is an optical heartrate sensor.
 3. The wearable device of claim 1, further comprising: afunctionality subsystem configured to provide from the wearable device afunctionality selected from among telling time, measuring of distancetraveled, providing calendar notifications, displaying text messages,and interacting with an automated assistant.
 4. The wearable device ofclaim 1 wherein the control logic is configured to activate the firstsensor for sampling periods that occur during the monitoring period. 5.The wearable device of claim 4 wherein the sampling periods amount to aminority of the length of the monitoring period.
 6. The wearable deviceof claim 4 wherein the sampling periods amount to no more than 10% ofthe length of the monitoring period.
 7. The wearable device of claim 4wherein the sampling periods amount to no more than 20% of the length ofthe monitoring period.
 8. The wearable device of claim 1, furthercomprising: a second sensor; and analysis logic configured to infer thatthe subject is in a sleep period based upon output of the second sensor.9. The wearable device of claim 1, further comprising: auser-activatable input device; and analysis logic configured todetermine that the subject is in a sleep period based upon inputreceived via the user-activatable input device.
 10. The wearable deviceof claim 1 wherein heart rate samples are produced by the first sensorwhen activated, further comprising a display device configured todisplay a resting heart rate determined for the subject based on theheart rate samples produced by the first sensor.
 11. The wearable deviceof claim 1 wherein heart rate samples are produced by the first sensorwhen activated, further comprising a communications subsystem configuredto transmit the heart rate samples produced by the first sensor to aseparate computing device.
 12. A method in a computing system fordetermining a minimum heart rate, comprising: initializing a currentminimum heart rate result; during a period when a wearer of a wearabledevice is determined to be in a sleep period: for each of a plurality ofsampling periods: obtaining via the wearable device a sequence of heartrate samples for the wearer; for each of the samples, assessing whetherthe sample is usable; if at least a threshold percentage of the samplesare assessed to be usable: aggregating the samples assessed to beusable; and if the aggregated samples are smaller than the currentminimum heart rate result, blend the aggregated samples into the currentminimum heart rate result.
 13. The method of claim 12 wherein theassessing, aggregating, and blending are performed on the wearabledevice.
 14. The method of claim 12 wherein the assessing, aggregating,and blending are performed on a computer system distinct from thewearable device.
 15. The method of claim 12 wherein obtained heart ratesamples span a monitoring period, the method further comprisingactivating a heart rate sensor in the wearable device during samplingperiods that collectively amount to a minority of the monitoring period.16. The method of claim 12, further comprising determining that thewearer is determined to be in a sleep period based upon explicit inputfrom the wearer.
 17. The method of claim 12, further comprisinginferring that the wearer is determined to be in a sleep period.
 18. Acomputer-readable medium storing a resting heart rate data structure fora subject, the data structure comprising: a plurality of entries, eachentry corresponding to a different sleep period of the subject, eachentry comprising: a quantitative indication of a resting heart rate forthe subject, the indication having been generated from heart ratesamples captured from the subject by a wearable device during the sleepperiod.
 19. The computer-readable medium of claim 18 wherein thequantitative indication of each entry has been generated from heart ratesamples captured from the subject by a wearable device during a minorityof the length of the sleep period.
 20. The computer-readable medium ofclaim 18 wherein the quantitative indication of each entry has beengenerated from heart rate samples filtered to exclude heart rate sampleshaving an inadequate quality level.